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DBMS > Databricks vs. GeoSpock vs. PouchDB vs. RDF4J

System Properties Comparison Databricks vs. GeoSpock vs. PouchDB vs. RDF4J

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeoSpock  Xexclude from comparisonPouchDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Spatial and temporal data processing engine for extreme data scaleJavaScript DBMS with an API inspired by CouchDBRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeRDF store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.databricks.comgeospock.compouchdb.comrdf4j.org
Technical documentationdocs.databricks.compouchdb.com/­guidesrdf4j.org/­documentation
DeveloperDatabricksGeoSpockApache Software FoundationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release201320122004
Current release2.0, September 20197.1.1, June 2019
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJavaScriptJava
Server operating systemshostedhostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnono
Secondary indexesyestemporal, categoricalyes infovia viewsyes
SQL infoSupport of SQLwith Databricks SQLANSI SQL for query only (using Presto)nono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCHTTP REST infoonly for PouchDB Server
JavaScript API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesPython
R
Scala
JavaScriptJava
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoView functions in JavaScriptyes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infowith a proxy-based framework, named couchdb-loungenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users can be defined per tablenono
More information provided by the system vendor
DatabricksGeoSpockPouchDBRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGeoSpockPouchDBRDF4J infoformerly known as Sesame
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